## 10.6 percent in 2022, with significant heterogeneity across countries—5.9 percent in France ## Source details **Canonical URL:** [10.6 percent in 2022, with significant heterogeneity across countries—5.9 percent in France](https://www.imf.org/-/media/files/publications/wp/2025/english/wpiea2025058-print-pdf.pdf) ## Other formats - [Markdown version](/-/media/files/publications/wp/2025/english/wpiea2025058-print-pdf.pdf.md) - [Structured JSON version](/-/media/files/publications/wp/2025/english/wpiea2025058-print-pdf.pdf.json) --- ### Background and motivation - Consumer price inflation reached 10.6 percent in 2022, with significant heterogeneity across countries—5.9 percent in France versus as high as 25.2 percent in the Baltics. - To bring inflation under control, the European Central Bank (ECB) increased short-term interest rates from a historical low of 0 percent in 2022 to 4.5 percent by the end of 2023. - With inflation moving toward the target, the ECB eased the monetary policy stance by 115 basis points to 3.15 percent as of December 2024. - The study focuses on identifying exogenous monetary policy shocks and quantifying their effects on output, inflation, and labor-market outcomes, using high-frequency data on online job vacancy postings for three eurozone countries (Estonia, Latvia and Lithuania) during the period 2018–2024. ### Data overview - Daily dataset covering Estonia, Latvia and Lithuania over the period 2018–2024. - Dependent variable: online job vacancy postings (7-day moving average used to smooth daily volatility) obtained from Lightcast (previously Burning Glass Technologies). - Lightcast extracts and codes job-level information (job title, employer, job location, occupation, industry, experience, skills, education requirements, and earnings), deduplicates postings, and assigns standardized industry and occupation codes. - Monetary policy shocks: daily changes in 6-months ahead Overnight Index Swap (OIS) rates around scheduled ECB monetary policy announcements, drawn from the Euro Area Monetary Policy Event-Study Database (EA-MPD). - Monetary event window: change computed as difference between median quote during 13:25-13:35 before the press release and median quote during 15:40-15:50 after the press conference. - Robustness: also consider 1-year and 2-year ahead OIS rates and the Krippner (2013) shadow interest rate. - COVID-19 policy controls: OxCGRT stringency index and economic support index (report a number between 0 to 100). ### Econometric methodology - Identification: ‘interest rate surprise’ approach using high-frequency changes in forward-looking OIS rates to capture unexpected monetary policy shocks. - Estimation method: local projections (LP) per Jordà (2005) with L = 30 (30 days of lagged values included). - Regression specification (summarized): - Dependent variable: cumulative change in online job vacancy postings h days after the shock, computed as log differences. - Main regressor: shock_t-1_ECB (daily change in 6-months ahead OIS during the monetary event window). - Controls: 30-day lags of dependent variable and monetary shocks, time-invariant country-specific effects, time fixed effects, OxCGRT indices in robustness checks. - Standard errors: Newey-West (1987) correction to address serial correlation induced by successive leadings of the dependent variable. - Impulse response functions (IRFs): estimated β_h for h = 0,..,30 days with 95 percent confidence bands. ### Key empirical findings - General effect: - A contractionary (expansionary) monetary policy shock causes a persistent decline (increase) in online job vacancy postings. - Across all countries, the average effect amounts to about 2 percent in 15 days after a contractionary monetary policy shock (i.e., an unanticipated increase of 1 percentage points in short-term interest rates). - An unexpected monetary easing leads to an increase of similar magnitude in online job vacancy postings. - Timing and persistence: - Marginal effect within the first 10 days; cumulative impact becomes economically significant and peaks after 15 days. - Effects weaken slowly and, depending on the country, disappear over the course of a month. - Cross-country heterogeneity: - Rate of contraction in online job vacancy postings after a 1 percentage point unanticipated tightening: - Latvia: 0.5 percent - Estonia: 2 percent - Lithuania: 3.2 percent - Persistence: negative effect is highly persistent in Lithuania; tends to disappear over the course of a month in Estonia and Latvia. - Identification considerations: - Baltic countries represent an extremely small share of euro area GDP, supporting the exogeneity of the ECB monetary stance for this context. - Announcement effects are acknowledged; they may be weaker in the Baltics due to desynchronized economic cycles relative to larger eurozone countries. ### Robustness checks - Alternative monetary shock measures: - Shadow rate constructed by Krippner (2013) used instead of the 6-month OIS rate produces qualitatively and quantitatively similar results. - Additional controls: - Inclusion of COVID-19 policy measures (OxCGRT stringency and economic support indices) yields qualitatively and quantitatively similar findings, with minor differences relative to the baseline. - Different OIS horizons: - Results robust to using 1-year and 2-year ahead OIS rates. ### Policy relevance and conclusions - Monetary policy has statistically and economically significant effects on labor markets as measured by online job vacancy postings in Estonia, Latvia and Lithuania over 2018–2024. - Key takeaways for policymakers: - An unanticipated 1 percentage point monetary tightening by the ECB reduces online job vacancy postings by about 2 percent on average after 15 days. - Effects vary substantially across countries in both magnitude and persistence (0.5 percent in Latvia, 2 percent in Estonia, 3.2 percent in Lithuania). - Daily high-frequency data and the interest rate surprise identification reveal the timing and heterogeneity of monetary transmission to labor-demand indicators. - Implication: empirical evidence is directly relevant to policymakers concerned with the transmission of monetary policy to labor-market outcomes. ### Appendix figures (descriptions) - Appendix Figure A1. Impact of Monetary Policy Shocks on Online Job Vacancy Postings (with the Krippner shadow rate) - Country-level displays for Estonia, Latvia, Lithuania. Note: Source: Authors’ estimations. - Appendix Figure A2. Impact of Monetary Policy Shocks on Online Job Vacancy Postings (with additional control variables) - Country-level displays for Estonia, Latvia, Lithuania. Note: Source: Authors’ estimations. *Source: IMF staff analysis (wpiea2025058-print-pdf).* ### 10.6 percent in 2022, with significant heterogeneity across countries—5.9 percent in France ### wpiea2025058-print-pdf - 10.6 percent in 2022, with significant heterogeneity across countries—5.9 percent in France ### Background and motivation - Consumer price inflation reached 10.6 percent in 2022, with significant heterogeneity across countries—5.9 percent in France versus as high as 25.2 percent in the Baltics. - To bring inflation under control, the European Central Bank (ECB) increased short-term interest rates from a historical low of 0 percent in 2022 to 4.5 percent by the end of 2023. - With inflation moving toward the target, the ECB eased the monetary policy stance by 115 basis points to 3.15 percent as of December 2024. - The study focuses on identifying exogenous monetary policy shocks and quantifying their effects on output, inflation, and labor-market outcomes, using high-frequency data on online job vacancy postings for three eurozone countries (Estonia, Latvia and Lithuania) during the period 2018–2024. ### Data overview - Daily dataset covering Estonia, Latvia and Lithuania over the period 2018–2024. - Dependent variable: online job vacancy postings (7-day moving average used to smooth daily volatility) obtained from Lightcast (previously Burning Glass Technologies). - Lightcast extracts and codes job-level information (job title, employer, job location, occupation, industry, experience, skills, education requirements, and earnings), deduplicates postings, and assigns standardized industry and occupation codes. - Monetary policy shocks: daily changes in 6-months ahead Overnight Index Swap (OIS) rates around scheduled ECB monetary policy announcements, drawn from the Euro Area Monetary Policy Event-Study Database (EA-MPD). - Monetary event window: change computed as difference between median quote during 13:25-13:35 before the press release and median quote during 15:40-15:50 after the press conference. - Robustness: also consider 1-year and 2-year ahead OIS rates and the Krippner (2013) shadow interest rate. - COVID-19 policy controls: OxCGRT stringency index and economic support index (report a number between 0 to 100). ### Econometric methodology - Identification: ‘interest rate surprise’ approach using high-frequency changes in forward-looking OIS rates to capture unexpected monetary policy shocks. - Estimation method: local projections (LP) per Jordà (2005) with L = 30 (30 days of lagged values included). - Regression specification (summarized): - Dependent variable: cumulative change in online job vacancy postings h days after the shock, computed as log differences. - Main regressor: shock_t-1_ECB (daily change in 6-months ahead OIS during the monetary event window). - Controls: 30-day lags of dependent variable and monetary shocks, time-invariant country-specific effects, time fixed effects, OxCGRT indices in robustness checks. - Standard errors: Newey-West (1987) correction to address serial correlation induced by successive leadings of the dependent variable. - Impulse response functions (IRFs): estimated β_h for h = 0,..,30 days with 95 percent confidence bands. ### Key empirical findings - General effect: - A contractionary (expansionary) monetary policy shock causes a persistent decline (increase) in online job vacancy postings. - Across all countries, the average effect amounts to about 2 percent in 15 days after a contractionary monetary policy shock (i.e., an unanticipated increase of 1 percentage points in short-term interest rates). - An unexpected monetary easing leads to an increase of similar magnitude in online job vacancy postings. - Timing and persistence: - Marginal effect within the first 10 days; cumulative impact becomes economically significant and peaks after 15 days. - Effects weaken slowly and, depending on the country, disappear over the course of a month. - Cross-country heterogeneity: - Rate of contraction in online job vacancy postings after a 1 percentage point unanticipated tightening: - Latvia: 0.5 percent - Estonia: 2 percent - Lithuania: 3.2 percent - Persistence: negative effect is highly persistent in Lithuania; tends to disappear over the course of a month in Estonia and Latvia. - Identification considerations: - Baltic countries represent an extremely small share of euro area GDP, supporting the exogeneity of the ECB monetary stance for this context. - Announcement effects are acknowledged; they may be weaker in the Baltics due to desynchronized economic cycles relative to larger eurozone countries. ### Robustness checks - Alternative monetary shock measures: - Shadow rate constructed by Krippner (2013) used instead of the 6-month OIS rate produces qualitatively and quantitatively similar results. - Additional controls: - Inclusion of COVID-19 policy measures (OxCGRT stringency and economic support indices) yields qualitatively and quantitatively similar findings, with minor differences relative to the baseline. - Different OIS horizons: - Results robust to using 1-year and 2-year ahead OIS rates. ### Policy relevance and conclusions - Monetary policy has statistically and economically significant effects on labor markets as measured by online job vacancy postings in Estonia, Latvia and Lithuania over 2018–2024. - Key takeaways for policymakers: - An unanticipated 1 percentage point monetary tightening by the ECB reduces online job vacancy postings by about 2 percent on average after 15 days. - Effects vary substantially across countries in both magnitude and persistence (0.5 percent in Latvia, 2 percent in Estonia, 3.2 percent in Lithuania). - Daily high-frequency data and the interest rate surprise identification reveal the timing and heterogeneity of monetary transmission to labor-demand indicators. - Implication: empirical evidence is directly relevant to policymakers concerned with the transmission of monetary policy to labor-market outcomes. *Source: IMF staff analysis (wpiea2025058-print-pdf).* ### Appendix Figure A1. Impact of Monetary Policy Shocks on Online Job Vacancy Postings ### Appendix Figure A1. Impact of Monetary Policy Shocks on Online Job Vacancy Postings (with the Krippner shadow rate) ### Country-level displays - Estonia - Figure caption: Impact of Monetary Policy Shocks on Online Job Vacancy Postings (with the Krippner shadow rate) - Note: Source: Authors’ estimations. - Latvia - Figure caption: Impact of Monetary Policy Shocks on Online Job Vacancy Postings (with the Krippner shadow rate) - Note: Source: Authors’ estimations. - Lithuania - Figure caption: Impact of Monetary Policy Shocks on Online Job Vacancy Postings (with the Krippner shadow rate) - Note: Source: Authors’ estimations. ### Appendix Figure A2. Impact of Monetary Policy Shocks on Online Job Vacancy Postings (with additional control variables) ### Country-level displays with additional controls - Estonia - Figure caption: Impact of Monetary Policy Shocks on Online Job Vacancy Postings (with additional control variables) - Note: Source: Authors’ estimations. - Latvia - Figure caption: Impact of Monetary Policy Shocks on Online Job Vacancy Postings (with additional control variables) - Note: Source: Authors’ estimations. - Lithuania - Figure caption: Impact of Monetary Policy Shocks on Online Job Vacancy Postings (with additional control variables) - Note: Source: Authors’ estimations. ### References cited in the Appendix figures - Acemoglu, D., D. Autor, J. Hazell, and P. Restrepo (2022). “Artificial Intelligence and Jobs: Evidence from Online Vacancies,” Journal of Labor Economics, Vol. 40, pp. 293–340. - Altavilla, C., L. Brugnolini, R. Gürkaynak, R. Motto, and G. 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